- Home
- A-Z Publications
- First Break
- Previous Issues
- Volume 40, Issue 5, 2022
First Break - Volume 40, Issue 5, 2022
Volume 40, Issue 5, 2022
-
-
Carbon Capture and Storage Potential in Ireland — Returning Carbon Whence It Came
Authors Joseph M. English and Kara L. EnglishSummaryCarbon capture and storage (CCS) involves the capture of CO2 emissions produced from industrial and electricity generation sources, followed by transport to permanent underground geological storage. Hence, CCS is one mitigation option available to achieve the targets set out in the Paris Agreement. Here we discuss CCS potential with particular reference to Ireland’s emission targets, policy positions and geological storage options. In Ireland, CCS could be utilised (1) with gas-powered electricity to provide secure and reliable low-emissions electricity, (2) to reduce emissions in hard-to-abate industries such as cement manufacturing, and (3) to facilitate the future deployment of negative emissions technologies. Ireland has significant potential to store CO2 in geological formations in depleted gas fields and deep saline aquifers in its offshore sedimentary basins. Two high-graded options are the offshore Kinsale Head and Corrib gas fields. Provisional estimates for the CO2 storage capacity of these two fields are 321 Mt and 44 Mt respectively. The depleted Kinsale Head gas field alone could have sufficient storage capacity to take the equivalent of up to 40 years of CO2 emissions from the top 10 point-source emitters in Ireland. Further work is needed to fully characterise and mature the potential for CCS in Ireland.
-
-
-
The Right Maturity Model for the Norwegian North Sea
Authors Karthik Iyer, Ebbe H. Hartz and Daniel W. SchmidAbstractVitrinite reflectance (VR) is routinely measured as an indicator of the thermal maturity of source rocks. Since the 1970s, algorithms that model VR have been used to calibrate thermal models. The modelled thermal history can vary significantly depending on the choice of VR model. Over the last few years, numerous VR models have been proposed and it is unclear which one should be used. The choice of the appropriate VR model is often left to the user or modelling software and is used without determining the suitability of the chosen model for the region or dataset. To avoid such biases, we explore a comprehensive VR dataset from the Norwegian North Sea to determine the VR model that best fits measurements. We use a 1D basin model that simulates VR in the well and combine it with global optimization algorithms to determine which of the currently favoured VR models fits the data best. We find that the Easy%Ro DL model best fits data from the Norwegian North Sea.
-
Volumes & issues
-
Volume 42 (2024)
-
Volume 41 (2023)
-
Volume 40 (2022)
-
Volume 39 (2021)
-
Volume 38 (2020)
-
Volume 37 (2019)
-
Volume 36 (2018)
-
Volume 35 (2017)
-
Volume 34 (2016)
-
Volume 33 (2015)
-
Volume 32 (2014)
-
Volume 31 (2013)
-
Volume 30 (2012)
-
Volume 29 (2011)
-
Volume 28 (2010)
-
Volume 27 (2009)
-
Volume 26 (2008)
-
Volume 25 (2007)
-
Volume 24 (2006)
-
Volume 23 (2005)
-
Volume 22 (2004)
-
Volume 21 (2003)
-
Volume 20 (2002)
-
Volume 19 (2001)
-
Volume 18 (2000)
-
Volume 17 (1999)
-
Volume 16 (1998)
-
Volume 15 (1997)
-
Volume 14 (1996)
-
Volume 13 (1995)
-
Volume 12 (1994)
-
Volume 11 (1993)
-
Volume 10 (1992)
-
Volume 9 (1991)
-
Volume 8 (1990)
-
Volume 7 (1989)
-
Volume 6 (1988)
-
Volume 5 (1987)
-
Volume 4 (1986)
-
Volume 3 (1985)
-
Volume 2 (1984)
-
Volume 1 (1983)